During the last decades, the use of advanced optimization algorithms to generate sports timetables has caught the attention of both academics and practitioners. From a managerial standpoint, the competition’s structure and the design of the league’s schedule represent key strategic decisions with a direct impact in terms of revenue and other important indicators. Argentina’s National Basketball League (LNB) has undergone a major transformation since 2014, implementing a tour-based schedule design to reduce the total distance traveled by the teams. In this work, we build upon this experience and evaluate the impact of an alternative league structure for the LNB, considering the interest of the games in a schedule as a key design element. We consider a league structure with a couple-based system and a time constrained schedule that
increases the share of games played during weekends. We introduce a metric to measure the interest of a game and explore different Integer Linear Programming (ILP) models to construct the schedule, including a new framework that partially incorporates the touring scheme into the time constrained schedule in a more controlled fashion. Throughout extensive computational experiments over six LNB seasons, we show that our framework reduces the traveled distance in most of the instances and that it translates into higher revenue under moderate stadium attendance assumptions, with increments reaching up to 40 percent.